Property and maintenance management framework for New Zealand's state schools: a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Construction at Massey University, Albany, New Zealand

School buildings and infrastructure are considered fundamental elements of any community. The buildings and infrastructure are not only supposed to provide a pleasant, and safe environment for staff and students, but they are also a clearly visible presentation of the education system. As a result, it is important to ensure that school properties are well maintained through proactive management. In New Zealand (NZ), state school properties are owned by the Ministry of Education (MoE) and managed and operated by the school board of each school with the assistance of external consultants. This research aims to develop a framework which helps those involved in managing school buildings and infrastructure in New Zealand's state schools by focusing on improving the collaboration among the key stakeholders. Previous research on managing existing property and associated theoretical concepts, such as asset management, property management, maintenance management, stakeholders’ involvement, and maturity model frameworks, were reviewed to identify research problems. In order to refine the research objectives, a preliminary study was conducted that involved the researcher attending training courses on property and maintenance management to understand processes, make connections, conduct interviews with other attendees, and distribute a survey among them. Findings from the preliminary study highlighted the central role of stakeholders’ collaboration for the provision of efficient property and maintenance management, but other issues were also identified. A further in-depth study based on interviews with school managers was undertaken to cover the current activities and processes, challenges, roles, and responsibilities of the key stakeholders in managing existing buildings and infrastructure in state schools in New Zealand. Based on findings from the literature review and interviews, a maturity assessment model was developed, and a questionnaire was distributed to explore the maturity levels of different management processes currently in place with the aim of identifying the priorities for process improvement actions. The maturity level scores revealed the most needed improvement areas that the key stakeholders should focus on, including the reporting system, performance evaluation, staff training, lesson sharing, communication, and continuous improvement. In addition, Partial Least Squares Structural Equation Modelling (PLS-SEM) approach was used to explore the relationships among key stakeholders and test the research hypotheses. The results of PLS-SEM assessment prove that there are undeniable relationships between the key stakeholders. This also highlighted that all stakeholders are responsible to work closely as a team as they have both direct and indirect effects on each other's performance. Close teamwork contributes to the overall outcome of property and maintenance management for NZ's state schools. A property and maintenance management framework for NZ's state schools was then developed based on the findings of the literature review, and data analysis using the key concepts of the Plan-Do-Check-Act cycle. The proposed framework comprises five stages (Establish, Plan, Implement, Evaluate, and Improve - E-PIE-I, and shortened to PIE) and includes activities in each stage. More activities were added in the Establish phase in order to address the need to provide staff training programmes and improve the collaboration between people involved in the processes. Moreover, the proposed PIE features a feedback loop in the Evaluate and Improve stages which helps assess performance of the processes and obtain feedback and learning outcomes for continuous improvements. Validation interviews with school managers were conducted and the results show that the PIE framework could help improve the property and maintenance management for New Zealand's state schools. The research contributes to the property and maintenance management field with a focus on the collaboration between the people involved in the process. The research also reveals other challenges and issues in managing school property in state schools and proposes solutions to overcome these challenges. More importantly, this research produces a set of diagrams in the PIE framework which can be used as guidelines for school managers and other stakeholders to perform their roles effectively. The study finally produces recommendations for improvements in managing school property at both the school and the MoE level. The findings should be of interest to top management, schools, service providers, and researchers dealing with the management of existing buildings and infrastructure in schools

Optimizing radial basis functions by D.C. programming and its use in direct search for global derivative-free optimization

In this paper we address the global optimization of functions subject to bound and linear constraints without using derivatives of the objective function. We investigate the use of derivative-free models based on radial basis functions (RBFs) in the search step of direct-search methods of directional type. We also study the application of algorithms based on difference of convex (d.c.) functions programming to solve the resulting subproblems which consist of the minimization of the RBF models subject to simple bounds on the variables. Extensive numerical results are reported with a test set of bound and linearly constrained problems

Programmation DC et DCA pour l'optimisation non convexe/optimisation globale en variables mixtes entières (Codes et Applications)

Basés sur les outils théoriques et algorithmiques de la programmation DC et DCA, les travaux de recherche dans cette thèse portent sur les approches locales et globales pour l'optimisation non convexe et l'optimisation globale en variables mixtes entières. La thèse comporte 5 chapitres. Le premier chapitre présente les fondements de la programmation DC et DCA, et techniques de Séparation et Evaluation (B&B) (utilisant la technique de relaxation DC pour le calcul des bornes inférieures de la valeur optimale) pour l'optimisation globale. Y figure aussi des résultats concernant la pénalisation exacte pour la programmation en variables mixtes entières. Le deuxième chapitre est consacré au développement d'une méthode DCA pour la résolution d'une classe NP-difficile des programmes non convexes non linéaires en variables mixtes entières. Ces problèmes d'optimisation non convexe sont tout d'abord reformulées comme des programmes DC via les techniques de pénalisation en programmation DC de manière que les programmes DC résultants soient efficacement résolus par DCA et B&B bien adaptés. Comme première application en optimisation financière, nous avons modélisé le problème de gestion de portefeuille sous le coût de transaction concave et appliqué DCA et B&B à sa résolution. Dans le chapitre suivant nous étudions la modélisation du problème de minimisation du coût de transaction non convexe discontinu en gestion de portefeuille sous deux formes : la première est un programme DC obtenu en approximant la fonction objectif du problème original par une fonction DC polyèdrale et la deuxième est un programme DC mixte 0-1 équivalent. Et nous présentons DCA, B&B, et l'algorithme combiné DCA-B&B pour leur résolution. Le chapitre 4 étudie la résolution exacte du problème multi-objectif en variables mixtes binaires et présente deux applications concrètes de la méthode proposée. Nous nous intéressons dans le dernier chapitre à ces deux problématiques challenging : le problème de moindres carrés linéaires en variables entières bornées et celui de factorisation en matrices non négatives (Nonnegative Matrix Factorization (NMF)). La méthode NMF est particulièrement importante de par ses nombreuses et diverses applications tandis que les applications importantes du premier se trouvent en télécommunication. Les simulations numériques montrent la robustesse, rapidité (donc scalabilité), performance et la globalité de DCA par rapport aux méthodes existantes.Based on theoretical and algorithmic tools of DC programming and DCA, the research in this thesis focus on the local and global approaches for non convex optimization and global mixed integer optimization. The thesis consists of 5 chapters. The first chapter presents fundamentals of DC programming and DCA, and techniques of Branch and Bound method (B&B) for global optimization (using the DC relaxation technique for calculating lower bounds of the optimal value). It shall include results concerning the exact penalty technique in mixed integer programming. The second chapter is devoted of a DCA method for solving a class of NP-hard nonconvex nonlinear mixed integer programs. These nonconvex problems are firstly reformulated as DC programs via penalty techniques in DC programming so that the resulting DC programs are effectively solved by DCA and B&B well adapted. As a first application in financial optimization, we modeled the problem pf portfolio selection under concave transaction costs and applied DCA and B&B to its solutions. In the next chapter we study the modeling of the problem of minimization of nonconvex discontinuous transaction costs in portfolio selection in two forms: the first is a DC program obtained by approximating the objective function of the original problem by a DC polyhedral function and the second is an equivalent mixed 0-1 DC program. And we present DCA, B&B algorithm, and a combined DCA-B&B algorithm for their solutions. Chapter 4 studied the exact solution for the multi-objective mixed zero-one linear programming problem and presents two practical applications of proposed method. We are interested int the last chapter two challenging problems: the linear integer least squares problem and the Nonnegative Mattrix Factorization problem (NMF). The NMF method is particularly important because of its many various applications of the first are in telecommunications. The numerical simulations show the robustness, speed (thus scalability), performance, and the globality of DCA in comparison to existent methods.ROUEN-INSA Madrillet (765752301) / SudocSudocFranceF